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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Methods of computer simulation of turbopump vibrations described in report. For aircraft and aerospace service, high-speed, high-performance turbomachinery should be as light in weight as possible. Certain amount of mass needed in turbomachine housing for stiffness. Report addresses question of how much extra weight is necessary. Analyses shows under certain conditions, flexible housing more stable than rigid one.
Computer aided design and computer aided manufacturing have the potential for greatly reducing the cost and lead time in the development of VLSI components. This potential paves the way for the design and fabrication of a wide variety of economically feasible high level functional units. It was observed that current computer systems have only a limited capacity to absorb new VLSI component types other than memory, microprocessors, and a relatively small number of other parts. The first purpose is to explore a system design which is capable of effectively incorporating a considerable number of VLSI part types and will both increase the speed of computation and reduce the attendant programming effort. A second purpose is to explore design techniques for VLSI parts which when incorporated by such a system will result in speeds and costs which are optimal. The proposed work may lay the groundwork for future efforts in the extensive simulation and measurements of the system's cost effectiveness and lead to prototype development.
A life cycle cost analysis of high efficiency cells was presented. Although high efficiency cells produce more power, they also cost more to make and are more susceptible to array hot-spot heating. Three different computer analysis programs were used: SAMICS (solar array manufacturing industry costing standards), PVARRAY (an array failure mode/degradation simulator), and LCP (lifetime cost and performance). The high efficiency cell modules were found to be more economical in this study, but parallel redundancy is recommended.
The Caltech Concurrent Computation Program wwhich studies basic issues in computational science is described. The research builds on initial work where novel concurrent hardware, the necessary systems software to use it and twenty significant scientific implementations running on the initial 32, 64, and 128 node hypercube machines have been constructed. A major goal of the program will be to extend this work into new disciplines and more complex algorithms including general packages that decompose arbitrary problems in major application areas. New high-performance concurrent processors with up to 1024-nodes, over a gigabyte of memory and multigigaflop performance are being constructed. The implementations cover a wide range of problems in areas such as high energy and astrophysics, condensed matter, chemical reactions, plasma physics, applied mathematics, geophysics, simulation, CAD for VLSI, graphics and image processing. The products of the research program include the concurrent algorithms, hardware, systems software, and complete program implementations.
The ongoing development of a tool for tactical guidance research and the analysis of airplane system performance in a tactically significant environment are described. The objective of the tool is to provide a means by which researchers can explore and exploit enhancements to high-performance airplane agility. The completed tool will include high-fidelity batch and piloted simulation capabilities, an advanced tactical guidance logic, and a user-friendly interface. While the tool is being developed for the purpose of studying fighter agility, its modularity should make it easily adaptable to the analysis of other technologies and, thus, be of interest to a number of potential users.
Hardware, software, and techniques used by the Fluid Dynamics Division (NASA) for performing visualization of computational aerodynamics, which can be applied to the visualization of flow fields from computer simulations of fluid dynamics about the Space Shuttle, are discussed. Three visualization techniques applied, post-processing, tracking, and steering, are described, as well as the post-processing software packages used, PLOT3D, SURF (Surface Modeller), GAS (Graphical Animation System), and FAST (Flow Analysis software Toolkit). Using post-processing methods a flow simulation was executed on a supercomputer and, after the simulation was complete, the results were processed for viewing. It is shown that the high-resolution, high-performance three-dimensional workstation combined with specially developed display and animation software provides a good tool for analyzing flow field solutions obtained from supercomputers.
It is noted that the types of technology required for computational physics are changing as the field matures. Emphasis has shifted from computer technology to algorithm technology and, finally, to visual analysis technology as areas of critical research for this field. High-performance graphical workstations tied to a supercommunicator with high-speed communications along with the development of especially tailored visualization software has enabled analysis of highly complex fluid-dynamics simulations. Particular reference is made here to the development of visual analysis tools at NASA's Numerical Aerodynamics Simulation Facility. The next technology which this field requires is one that would eliminate visual clutter by extracting key features of simulations of physics and technology in order to create displays that clearly portray these key features. Research in the tuning of visual displays to human cognitive abilities is proposed. The immediate transfer of technology to all levels of computers, specifically the inclusion of visualization primitives in basic software developments for all work stations and PCs, is recommended.
Current research in high-efficiency, high-performance traveling wave tubes (TWT's) has led to the development of novel thermal/ mechanical computer models for use with helical slow-wave structures. A three-dimensional, finite element computer model and analytical technique used to study the structural integrity and thermal operation of a high-efficiency, diamond-rod, K-band TWT designed for use in advanced space communications systems. This analysis focused on the slow-wave circuit in the radiofrequency section of the TWT, where an inherent localized heating problem existed and where failures were observed during earlier cold compression, or 'coining' fabrication technique that shows great potential for future TWT development efforts. For this analysis, a three-dimensional, finite element model was used along with MARC, a commercially available finite element code, to simulate the fabrication of a diamond-rod TWT. This analysis was conducted by using component and material specifications consistent with actual TWT fabrication and was verified against empirical data. The analysis is nonlinear owing to material plasticity introduced by the forming process and also to geometric nonlinearities presented by the component assembly configuration. The computer model was developed by using the high efficiency, K-band TWT design but is general enough to permit similar analyses to be performed on a wide variety of TWT designs and styles. The results of the TWT operating condition and structural failure mode analysis, as well as a comparison of analytical results to test data are presented.
Recent results in the development of high-efficiency, low-bandgap GaInAsP solar cells epitaxially grown and lattice matched on InP substrates are presented. Such cells are intended to be used as optimum bottom cell components in tandem solar cells. Assuming that a GaAs-based top cell is used, computer simulation of the potential bottom cell performance as a function of the cell bandgap and incident spectrum indicates that two particular alloys are desirable: Ga0.47In0.53As (Eg = 0.75 eV) for space applications and Ga0.25In0.75As0.54P0.46 (Eg = 0.95 eV) for terrestrial applications. In each of these materials, solar cells with new record-level efficiencies have been fabricated. The efficiency boost available to tandem configurations from these low-bandgap cells is discussed.
An architecture has been developed for a high-performance VLSI digital signal processor that is highly reliable, fault-tolerant, and radiation-hard. The signal processor, part of a spacecraft receiver designed to support uplink radio science experiments at the outer planets, organizes the connections between redundant arithmetic resources, register files, and memory through a shuffle exchange communication network. The configuration of the network and the state of the processor resources are all under microprogram control, which both maps the resources according to algorithmic needs and reconfigures the processing should a failure occur. In addition, the microprogram is reloadable through the uplink to accommodate changes in the science objectives throughout the course of the mission. The processor will be implemented with silicon compiler tools, and its design will be verified through silicon compilation simulation at all levels from the resources to full functionality. By blending reconfiguration with redundancy the processor implementation is fault-tolerant and reliable, and possesses the long expected lifetime needed for a spacecraft mission to the outer planets.
Current research in high-efficiency, high-performance traveling wave tubes (TWT's) has led to the development of novel thermal/mechanical computer models for use with helical slow-wave structures. A three-dimensional, finite element computer model and analytical technique used to study the structural integrity and thermal operation of a high-efficiency, diamond-rod, K-band TWT designed for use in advanced space communications systems. This analysis focused on the slow-wave circuit in the radiofrequency section of the TWT, where an inherent localized heating problem existed and where failures were observed during earlier cold compression, or 'coining' fabrication technique that shows great potential for future TWT development efforts. For this analysis, a three-dimensional, finite element model was used along with MARC, a commercially available finite element code, to simulate the fabrication of a diamond-rod TWT. This analysis was conducted by using component and material specifications consistent with actual TWT fabrication and was verified against empirical data. The analysis is nonlinear owing to material plasticity introduced by the forming process and also to geometric nonlinearities presented by the component assembly configuration. The computer model was developed by using the high efficiency, K-band TWT design but is general enough to permit similar analyses to be performed on a wide variety of TWT designs and styles. The results of the TWT operating condition and structural failure mode analysis, as well as a comparison of analytical results to test data are presented.
This report contains numerous color illustrations to describe the NASA programs in aeronautics. The basic ideas involved are explained in brief paragraphs. The seven chapters deal with Subsonic aircraft, High-speed transport, High-performance military aircraft, Hypersonic/Transatmospheric vehicles, Critical disciplines, National facilities and Organizations & installations. Some individual aircraft discussed are : the SR-71 aircraft, aerospace planes, the high-speed civil transport (HSCT), the X-29 forward-swept wing research aircraft, and the X-31 aircraft. Critical disciplines discussed are numerical aerodynamic simulation, computational fluid dynamics, computational structural dynamics and new experimental testing techniques.
This paper describes the application of nonlinear quadratic regulator (NLQR) theory to the design of control laws for a typical high-performance aircraft. The NLQR controller design is performed using truncated solutions of the Hamilton-Jacobi-Bellman equation of optimal control theory. The performance of the NLQR controller is compared with the performance of a conventional P + I gain scheduled controller designed by applying standard frequency response techniques to the equations of motion of the aircraft linearized at various angles of attack. Both techniques result in control laws which are very similar in structure to one another and which yield similar performance. The results of applying both control laws to a high-g vertical turn are illustrated by nonlinear simulation.
A high-performance graphics workstation has been combined with software developed for flow-field visualization to yield a highly effective tool for analysis of fluid-flow dynamics. After the flow fields are obtained from experimental measurements or computer simulations, the workstation permits one to interactively view the dynamics of the flow fields; e.g., the viewer can zoom into a region or rotate his viewing position about the region to study it in more detail. Several techniques for visualization of flow fields with this workstation are described in this paper and illustrated with a videotape available from the authors. The computer hardware and software required to create effective flow visualization displays are discussed. Additional software and hardware required to create videotapes or 16mm movies are also described. Limitations imposed by current workstation performance is addressed and future workstation performance is forecast.
As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.
Active learning algorithms, integrating machine learning, quantum computing and optics simulation in an iterative loop, offer a promising approach to optimizing metamaterials. However, these algorithms can face difficulties in optimizing highly complex structures due to computational limitations. High-performance computing (HPC) and quantum computing (QC) integrated systems can address these issues by enabling parallel computing. In this study, we develop an active learning algorithm working on HPC-QC integrated systems. We evaluate the performance of optimization processes within active learning (i.e., training a machine learning model, problem-solving with quantum computing, and evaluating optical properties through wave-optics simulation) for highly complex metamaterial cases. Our results showcase that utilizing multiple cores on the integrated system can significantly reduce computational time, thereby enhancing the efficiency of optimization processes. Therefore, we expect that leveraging HPC-QC integrated systems helps effectively tackle large-scale optimization challenges in general.
The design of moisture-durable building enclosures with low embodied carbon often involves an iterative process of selecting the materials for the specific exposure conditions to meet the performance requirements. While hygrothermal simulations are commonly used to evaluate moisture durability, they often require advanced expertise for proper implementation. Machine learning (ML) provides a promising alternative by streamlining the design process and minimizing the reliance on complex simulations. This study presents a machine learning-based approach for predicting moisture durability in residential wall assemblies. The ML model was trained to estimate the mold index and maximum moisture content of various layers under typical exposure conditions. The model achieved a high predictive accuracy, with a coefficient of determination (R²) exceeding 0.90 when compared to traditional hygrothermal simulations on materials that were not part of training the ML model. Building on these results, the ML model was developed into a practical tool for optimizing wall assembly designs. This tool allows users to automatically optimize material selections based on energy, moisture, and carbon performance criteria. By incorporating multi-objective optimization, the tool identifies configurations that minimize embodied carbon while maintaining moisture safety and code-compliant thermal performance. Additionally, it provides insights into how material choices influence assembly durability, energy efficiency, and carbon reduction. The tool will be implemented in the Building Science Advisor (BSA) to enhance its performance and provide more granularity on the results. This research highlights the potential for ML-driven tools to simplify the design of high-performance building enclosures, offering architects and engineers a faster, more efficient way to balance critical performance factors.
As the nuclear energy sector advances toward next-generation reactors, the need for high-performance fuel cladding materials has become increasingly urgent. Traditional alloys like zirconium and stainless steel are reaching their performance limits under higher temperatures, more corrosive coolants, and extended irradiation. This report presents the development of a new class of fuel cladding materials based on Non-Concentrated Alloys (NCAs) ? multi-element systems designed to deliver enhanced mechanical strength, corrosion resistance, and radiation tolerance. Through a combination of computational modeling (Computer Coupling of Phase Diagrams and Thermochemistry: CALPHAD), simulation-guided alloy selection, and experimental fabrication via arc melting and spark plasma sintering (SPS), three strategic alloy design paths were explored: (1) FeCrAl-based NCAs, (2) refractory-lean neutron-efficient alloys, and (3) equimolar high-entropy compositions. Microstructural analysis confirmed the formation of stable body-centered cubic BCC_A2 phases, while mechanical testing demonstrated hardness values significantly exceeding those of conventional cladding materials. The results highlight the tunability of NCA systems and their potential for balancing strength and ductility ? a critical consideration for in-reactor performance. Looking forward, future work will focus on thermomechanical optimization, CALPHAD refinement, and benchmarking against industry standards to enable scalable deployment. This work not only advances the science of nuclear materials but also supports broader goals in nuclear safety, performance, and nuclear energy innovation.